China provides an increasing amount of development finance to Africa; yet, little is known about the scale and distribution of its funding. AidData's interactive web-map allows researchers, policymakers, journalists, and citizens answer critical questions about where and how China is investing in African development.
Use the dashboard to search and share information on nearly 2,000 Chinese-backed projects in Africa from 2000-2012. Explore the data in a more granular way by drilling down to what is going on at a province, district, and street corner level. Compare China’s funding for development with other spatial data — on poverty, population, economic development — to identify relationships that would otherwise be difficult to uncover.
Contribute to the dialogue on Chinese impact in Africa by providing comments on project locations or help us refine our data by suggesting new development projects we may have missed, vetting existing records, or adding multimedia content.
The dashboard currently includes projects from the China Official Finance in Africa dataset (version 1.2) and the China in Ecological Hotspots dataset (version 1.0). We are hoping to add sub-national location information on projects from the China Global Official Finance dataset soon.
Using household survey data, Harvest Choice has produced a sub-national map displaying the density of individuals living on $2 or less a day (data from 2005). Because the survey from which these data were generated did not take place in North Africa or Zimbabwe, these countries are missing in this layer.
The Nighttime Lights approximates levels of economic development by using satellites to capture the luminosity of different geographic areas. Since 2000, the dataset has been used as a proxy variable for economic development in over 3,000 studies. In the absence of reliable data on income and other economic indicators, Nighttime Lights is able to show relative economic activity across a region.
The WorldPop project aggregates a range of open geospatial datasets on population (methods described here
) to generate estimates of population distribution in developing countries. Statistical assessments suggest that the resultant maps are consistently more accurate than existing population map products, as well as the simple gridding of census data. Moreover, the 100m spatial resolution represents a finer mapping detail than has been produced at national extents, and the integration with household survey, microdata, satellite and other datasources enables the production of more than simply population count estimates - age structures, births, pregnancies, poverty and urban growth are all mapped, with further variables under production.
ACLED (Armed Conflict Location and Event Data Project) provides one of the most comprehensive public collection of political violence data for developing states. These dataset contains information on the specific dates and locations of political violence, the types of event, the groups involved, fatalities and changes in territorial control. Information is recorded on the battles, killings, riots, and recruitment activities of rebels, governments, militias, armed groups, protesters and civilians. Event data are derived from a variety of sources including reports from developing countries and local media, humanitarian agencies, and research publications. The layer based on ACLED was generated by summing the number of fatalities from armed conflict events for every administrative (level 2) district in Africa.
CCAPS researchers at the University of North Texas and the University of Denver have produced a new resource which augments the ability of policymakers and researchers to analyze conflict patterns and possible intervention strategies in Africa. While previous data sources have focused on large-scale conflicts like civil and international wars, SCAD catalogues the myriad ways conflict manifests as political and social disorder. SCAD includes protests, riots, strikes, inter-communal conflict, government violence against civilians, and other forms of social conflict not systematically tracked in other conflict datasets. SCAD currently includes information on over 10,300 social conflict events from 1990 to 2012, and it will be periodically updated. The layer based on SCAD was generated by summing the number of social conflict participants for every administrative (level 2) district in Africa.
MRDS is a collection of reports describing metallic and nonmetallic mineral resources throughout the world. Included are deposit name, location, commodity, deposit description, geologic characteristics, production, reserves, resources, and references. It subsumes the original MRDS and MAS/MILS.
Other Spatial Features
development finance, or mapping the precise locations of development finance activities at the sub-national level, makes it easier for governments, donors, and citizens to visualize precisely where funding is directed. AidData has worked with Uppsala University’s Conflict Data Program
to develop a comprehensive geocoding methodology
that is both rigorous and flexible enough to be applied to all development projects. The methodology is referenced in the International Aid Transparency Initiative
(IATI) data standard and can be downloaded for use by any organization at open.aiddata.org.
Suggest a Project:
By right clicking on a particular location, users can suggest new Chinese aid or development finance projects that our research team might have missed. All suggested projects will be reviewed by a member of our research team before being published on the dashboard.
LERN is an Ushahidi-based, citizen feedback platform that allows users to submit real time reports about a range of social, political and economic events including: ethnic violence, discrimination, disease outbreak, protests, land disputes, workplace violence and infrastructure conditions. The organization collects these reports through SMS or online feedback and collates them into a single spatial dataset. For the purposes of this dashboard, our team keyword searched the citizen reports for any information related to China. While this can provide some additional context for location conditions in Liberia, these data should also be viewed as an example case for the type of crowdsourced citizen feedback that can be gathered and displayed through this dashboard.
User-contributed Multimedia Content:
In addition to enabling users to suggest new projects and comment or critique existing records, the dashboard will also allow users contribute photo of video evidence of a project. To add multimedia content to a project right-click on a geocode to comment, click "Choose File" and browser your computer for the content you want to upload. Like other crowd feedback, multimedia content will be reviewed by a member of the research team before being published.
This dashboard was made possible with funding from Humanity United.
DisclaimerThis dashboard is designed to
facilitate exploration and use of Chinese development finance data by a wide
variety of stakeholders. Please note that analysis or visualization of the data
published by independent users does not necessarily reflect the views of AidData,
and care must be exercised in using and interpreting the data on this website.